similar to: weighted quantiles

Displaying 20 results from an estimated 3000 matches similar to: "weighted quantiles"

2005 Oct 12
2
subsetting with by() or other function??
I think I must be missing something obvious, but I'm having trouble getting a data transformation to work on groupings of data within a data frame (csss3) as defined by 2 factors (population, locid). The data are sorted by year within locid within population and I want to lag another variable (dbc), i.e, shift them down by 1 row replacing the first row with NA, within groups defined by
2012 Nov 30
1
Fw: quantreg installation and conflicts with R 2.15.2
Just noticed that I get a similar error about object 'kronecker' in "Matrix" package when trying to load "lme4". So this is a more pervasive problem. Brian Brian S. Cade, PhD U. S. Geological Survey Fort Collins Science Center 2150 Centre Ave., Bldg. C Fort Collins, CO 80526-8818 email: brian_cade@usgs.gov tel: 970 226-9326 ----- Forwarded by Brian S
2012 Apr 19
2
ANOVA in quantreg - faulty test for 'nesting'?
I am trying to implement an ANOVA on a pair of quantile regression models in R. The anova.rq() function performs a basic check to see whether the models are nested, but I think this check is failing in my case. I think my models are nested despite the anova.rqlist() function saying otherwise. Here is an example where the GLM ANOVA regards the models as nested, but the quantile regression ANOVA
2011 Jul 21
2
Quantreg-rq crashing trouble
Hi I am using the quantreg package for median regression for a large series of subsets of data. It works fabulously for all but one subset. When it reaches this subset, R takes the command and never responds. I end up having to kill R and restart it. It appears to be something with the particular data subset, but I can't pinpoint the problem. Here are some details Operating system:
2006 Feb 21
3
How to get around heteroscedasticity with non-linear leas t squares in R?
Your understanding isn't similar to mine. Mine says robust/resistant methods are for data with heavy tails, not heteroscedasticity. The common ways to approach heteroscedasticity are transformation and weighting. The first is easy and usually quite effective for dose-response data. The second is not much harder. Both can be done in R with nls(). Andy From: Quin Wills > > I am
2017 Dec 05
2
warnings about factor levels dropped from predict.glm
I am helping a student with some logistic regression analyses and we are getting some strange inconsistencies regarding a warning about factor levels being dropped when running predict.glm(, newdata = ournewdata) on the logistic regression model object. We have checked multiple times that the factor levels have been defined similarly on both data sets (one used to estimate model and the newdata)
2007 Mar 19
1
likelihoods in SAS GENMOD vs R glm
List: I'm helping a colleague with some Poisson regression modeling. He uses SAS proc GENMOD and I'm using glm() in R. Note on the SAS and R output below that our estimates, standard errors, and deviances are identical but what we get for likelihoods differs considerably. I'm assuming that these must differ just by some constant but it would be nice to have some confirmation
2005 Nov 22
3
modifying code in contributed libraries - changes from versions 1.* to 2.*
Having finally updated from R 1.91 to R 2.2.0 with my installation of a new computer, I discovered that something has changed drastically about the way code for contributed packages is stored when installed in a local version of R. In the 1.* versions it was easy for me to go in and modify some of the code for a contributed package by using a text editor to change the script files (these
2005 Feb 23
2
stopping a function
I've looked for this information in all the R help sources I could find and found nothing. Is it possible to use some function key to stop the execution of some R command without ending the R session (Windows, R 1.91)? I've several times started functions that for various reasons are not executing properly and it would be nice to stop them without killing the R session. I've been
2018 Jan 12
1
glm$effects
I know I must be missing something obvious, but checking help and googling a bit did not turn up a useable answer. When I've estimated a glm() model object (my example is with just identity link with gaussian family so I could have used lm() instead), one of the terms returned in the model object is listed as $effects. What are these quantities? I have not been able to relate them to the
2016 Apr 15
1
Heteroscedasticity in a percent-cover dataset
Hi, I am currently trying to do a GLMM on a dataset with percent cover of seagrass (dep. var) and a suite of explanatory variables including algal (AC) and epiphyte cover (EC), rainfall, temperature and sunshine hours. M2=glmer(SG~AC+EC+TP+SS+RF+(1|Location/fSi/fTr), family=binomial,data=data,nAGQ=1) As the dependent variable is percent cover, I used a binomial error structure. I also have a
2012 Nov 30
1
quantreg installation and conflicts with R 2.15.2
I recently lost the partitions on my hard drive (second time in 6 months) so I had to have our IT folks image all my files over to a new drive. I completely reinstalled R (now 2.15.2) and all my libraries to my computer (Dell Latitude running Windows 7). A few of my previous workspaces (created with R 2.14.1) can't be restored, reporting an error similar to the one I get when I try to
2017 Dec 05
0
warnings about factor levels dropped from predict.glm
A guess (treat accordingly): Different BLAS versions are in use on the two different machines/versions. In one, near singularities are handled, and in the other they are not, percolating up to warnings at the R level. You can check this by seeing whether the estimated fit is the same on the 2 machines. If so, ignore the above. -- Bert Bert Gunter "The trouble with having an open mind
2007 Nov 16
1
graphics - line resolution/pixelation going from R to windows metafile
I have a recurring graphics issue that I've not been able to resolve with R. If I make a series of regression estimates and then plot the estimated function for the regression lines over a scatter plot of the data, e.g., using a sequence of plot( ) and lines ( ) similar to those below
2009 May 22
1
Goodness of fit in quantile regression
Dear R users, I've used the function qr.fit.sfn to estimate a quantile regression on a panel data set. Now I would like to compute an statistic to measure the goodness of fit of this model. Does someone know how could I do that? I could compute a pseudo R2 but in order to do that I would need the value of the objetive function at the optimum and I don't see how to get this from the
2018 Feb 20
1
question regarding the AICcmodavg package
Dear moderator, If possible I would like to send in the following question for R-help: I am analyzing a small data set using PGLS with phylogenetic uncertainty taken into account and thereby including 100 potential phylogenetic tree scenarios. I've managed to run models on all of the different trees and performed model averaging to get parameter estimates for the intercept and most of the
2009 May 29
3
Quantile GAM?
R-ers: I was wondering if anyone had suggestions on how to implement a GAM in a quantile fashion? I'm trying to derive a model of a "hull" of points which are likely to require higher-order polynomial fitting (e.g. splines)-- would quantreg be sufficient, if the response and predictors are all continuous? Thanks! --j
2010 Mar 30
2
weighted.median function from package R.basic
Dear all, I want to apply a weighted median on a huge dataset, and I remember a function from the package R.basic that could do this using an internal sorting algorithm qsort. This speeded things up quite a bit. Alas, I can't find that package anywhere anymore. There is a weighted.median function in the package limma too, but I didn't use that before. Anybody who knows what happened to
2006 Aug 03
3
Looking for transformation to overcome heterogeneity of variances
Dear All My data consists in 96 groups, each one with 10 observations. Levene's test suggests that the variances are not equal, and therefore I have tried to apply the classical transformations to have homocedasticity in order to be able to use ANOVA. Unfortunately, no transformation that I have used transforms my data into data with homocedasticity. The histogram of variances is at
2006 Mar 28
1
non parametric MANOVA
Dear colleagues, has anyone an idea how to carry out a nonparametric manova for comparing K groups? has anyone a good package of non-parametric stats? Thank you for your help. -- José David Gómez Químico Farmacéutico Universidad Nacional [[alternative HTML version deleted]]